style: Ignore some type errors (#370)

* Add comment to ignore mypy errors in _nash_mtl.py
* Add comment to ignore type error in mgda
* Add comment to ignore type error in TensorDict immutability tricks, and add a comment

Author: ValerianRey

src/torchjd/_autojac/_transform/_tensor_dict.py

@@ -32,16 +32,18 @@ def _check_key_value_pair(key: Tensor, value: Tensor) -> None:
     # Make TensorDict immutable, following answer in
     # https://stackoverflow.com/questions/11014262/how-to-create-an-immutable-dictionary-in-python
     # coming from https://peps.python.org/pep-0351/
+    # Note that this is not a perfect solution, because it breaks Liskov Substitution Principle, but
+    # it works.
     def _raise_immutable_error(self, *args, **kwargs) -> None:
         raise TypeError(f"{self.__class__.__name__} is immutable.")
 
     __setitem__ = _raise_immutable_error
     __delitem__ = _raise_immutable_error
     clear = _raise_immutable_error
-    update = _raise_immutable_error
-    setdefault = _raise_immutable_error
-    pop = _raise_immutable_error
-    popitem = _raise_immutable_error
+    update = _raise_immutable_error  # type: ignore[assignment]
+    setdefault = _raise_immutable_error  # type: ignore[assignment]
+    pop = _raise_immutable_error  # type: ignore[assignment]
+    popitem = _raise_immutable_error  # type: ignore[assignment]
 
 
 class Gradients(TensorDict):

src/torchjd/aggregation/_mgda.py

@@ -77,7 +77,7 @@ def forward(self, gramian: Tensor) -> Tensor:
             elif b <= a:
                 gamma = 0.0
             else:
-                gamma = (b - a) / (b + c - 2 * a)
+                gamma = (b - a) / (b + c - 2 * a)  # type: ignore[assignment]
             alpha = (1 - gamma) * alpha + gamma * e_t
             if gamma < self.epsilon:
                 break

src/torchjd/aggregation/_nash_mtl.py

@@ -23,6 +23,8 @@
 # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 # SOFTWARE.
 
+# mypy: ignore-errors
+
 from ._utils.check_dependencies import check_dependencies_are_installed
 from ._weighting_bases import Matrix, Weighting